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From James Taylor <jamestay...@apache.org>
Subject Re: RE: Local index related data bulkload
Date Fri, 12 Sep 2014 01:57:52 GMT
Hi Sun,
Yes, that explains it. With immutable indexes, there is no index
maintenance required, so there's no processing at all on the server side.
If your data is write-once/append-only, then immutable indexes are about as
efficient as you'll get. Any reason why you'd want to change them to local
indexes? Local indexes is an alternative to global indexes for *mutable*
data.
Thanks,
James

On Thu, Sep 11, 2014 at 6:51 PM, sunfl@certusnet.com.cn <
sunfl@certusnet.com.cn> wrote:

> Hi, Rajeshbabu
> Best appreciated for your kind reply and explaination. Exactly, we created
> only one local index for the table.
>
> We have one question: as far as we are concerned, for local indexing the
> index data may be already prepared
>
> for client upsert? Maybe there is no need to scan and search for specified
> regionserver processing? Cause we
>
> did not had so much trouble for the case of global index loading (no
> matther one index or more indexes related
>
> data loading).
>
> Another question. Gloable index we created are immutable indexes as
> setting IMMUTABLE_ROWS=true, while
> local indexing are default mutable indexes. Are these differences meaning
> a lot for the performance diversity?
>
> Best thanks,
> Sun
>
> ------------------------------
> ------------------------------
>
>
> *发件人:* rajeshbabu chintaguntla <rajeshbabu.chintaguntla@huawei.com>
> *发送时间:* 2014-09-11 23:45
> *收件人:* user@phoenix.apache.org
> *主题:* RE: Re: Local index related data bulkload
> Hi Sun,
>  The code snippet(*PhoenixIndexBuilder#batchStarted*) you have pointed
> out is not specific to local indexing, generic for any index. The main idea
> of the method is to keep the rows to index in block cache. So next time
> when ever scan the rows while preparing index updates we can get it from
> cache.
>          // The entire purpose of this method impl is to get the existing
> rows for the
>          // table rows being indexed into the block cache, as the index
> maintenance code
>          // does a point scan per row
>
>   This gives good performance when a table has more than one index.  One
> more thing with psql tool we do upserts in batches and each batch have 1000
> updates by default(if you don't specify any value to
> phoenix.mutate.batchSize). Lets suppose if all the rows are different we
> scan the region until we cache all the 1000 records. That's why
>   hasMore = scanner.nextRaw(results);     //Here....  might be taking
> more time.
> Can you tell me how many indexes you have created? One improvement we can
> do here is if we have only one index we can skip the scan in
> *PhoenixIndexBuilder#batchStarted. *
>
>  @James, currently we are scanning the data region while preparing index
> updates?why don't we prepare them without scanning data region if we can
> have get all index columns data from hooks?
>
>
>  bq. If someone had successfully done loading data through CsvBulkload
> using Spark and HDFS, please provide us more kindly suggesion.
>  Please refer "http://phoenix.apache.org/bulk_dataload.html#Loading via
> MapReduce" to run the bulkload from HDFS. Here we can pass index table to
> build as --index-table parameter.
>  But currently there is a problem with local indexing. I will raise an
> issue and work on it.
>
>
>  Thanks,
>  Rajeshbabu.
>
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>   ------------------------------
> *From:* sunfl@certusnet.com.cn [sunfl@certusnet.com.cn]
> *Sent:* Thursday, September 11, 2014 6:34 AM
> *To:* user
> *Subject:* Re: Re: Local index related data bulkload
>
>   Very thanks.
>
>  ------------------------------
>  ------------------------------
>
>
>     *From:* rajesh babu Chintaguntla <chrajeshbabu32@gmail.com>
> *Date:* 2014-09-10 21:09
> *To:* user@phoenix.apache.org
> *Subject:* Re: Local index related data bulkload
>   Hi Sun I am not accessible to code. Tomorrow morning I will check and
> let you know.
>
>  Thanks,
> Rajeshbabu
>
> On Wednesday, September 10, 2014, sunfl@certusnet.com.cn <
> sunfl@certusnet.com.cn> wrote:
>
>>  Any available suggestion?
>>
>>  ------------------------------
>>
>>    *发件人:* sunfl@certusnet.com.cn <http://UrlBlockedError.aspx>
>> *发送时间:* 2014-09-09 14:24
>> *收件人:* user <http://UrlBlockedError.aspx>
>> *主题:* 回复: Local index related data bulkload
>>   BTW.
>> The stacktrace info illustrates that our job running performance
>> bottleneck mainly lies in the following code :
>>      region.startRegionOperation();
>>           try {
>>                boolean hasMore;
>>                do {
>>                   List<Cell> results = Lists.newArrayList();
>>              // Results are potentially returned even when the return
>> value of s.next is false
>>              // since this is an indication of whether or not there are
>> more values after the
>>             // ones returned
>>                  hasMore = scanner.nextRaw(results);     //Here....
>>               } while (hasMore);
>>             } finally {
>>                try {
>>                  scanner.close();
>>                } finally {
>>                   region.closeRegionOperation();
>>                 }
>>             }
>>          }
>>
>>  ------------------------------
>>
>>    *发件人:* sunfl@certusnet.com.cn <http://UrlBlockedError.aspx>
>> *发送时间:* 2014-09-09 14:18
>> *收件人:* user <http://UrlBlockedError.aspx>
>> *抄送:* rajeshbabu chintaguntla <http://UrlBlockedError.aspx>
>> *主题:* Local index related data bulkload
>>   Hi all and rajeshbabu,
>>    Recently our job has encountered severe problems with trying to load
>> data with local indexes
>> into phoenix. The data load performance looks very bad compared with our
>> previous data
>> loading with gloable indexes. That seems quite absurd because phoenix
>> local index targets
>> scenarios with heavy write and space constraint use case, which is just
>> our job application.
>>    Observing stack trace during our job running, we can find the
>> following info:
>>
>>
>>  We then refer to the org.apache.phoenix.index.PhoenixIndexBuilder and
>> commented the batchStarted method. After recompiling the phoenix and
>> restart cluster,
>> our job loading performance get significant advance. Following is the
>> code for batcStarted method:
>> Here are my questions:
>> 1 Can these code committor explain the concrete functionality for this
>> method? Especially concerning to local index data loading...
>> 2 If we modify these codes (e.g. comment this method like what we do),
>> are there any potential influence for phoenix work?
>> 3 More helpful work..Can any guys share their codes about how to
>> complete data bulkload with local indexes while data file are storaged
>> within HDFS?
>> I know that CsvBulkload can do index related data upserting while
>> map-reduce bulkload didnot support that. Maybe our job is more likely to
>> map-refuce bulkload? So, If someone
>> had successfully done loading data through CsvBulkload using Spark and
>> HDFS, please provide us more kindly suggesion.
>>
>>  Best Regards,
>> Sun
>>
>>  /**
>> * Index builder for covered-columns index that ties into phoenix for
>> faster use.
>> */
>> public class PhoenixIndexBuilder extends CoveredColumnsIndexBuilder {
>>
>> @Override
>> public void batchStarted(MiniBatchOperationInProgress<Mutation>
>> miniBatchOp) throws IOException {
>> // The entire purpose of this method impl is to get the existing rows for
>> the
>> // table rows being indexed into the block cache, as the index
>> maintenance code
>> // does a point scan per row
>> List<KeyRange> keys =
>> Lists.newArrayListWithExpectedSize(miniBatchOp.size());
>> List<IndexMaintainer> maintainers = new ArrayList<IndexMaintainer>();
>> for (int i = 0; i < miniBatchOp.size(); i++) {
>> Mutation m = miniBatchOp.getOperation(i);
>> keys.add(PDataType.VARBINARY.getKeyRange(m.getRow()));
>> maintainers.addAll(getCodec().getIndexMaintainers(m.getAttributesMap()));
>> }
>> Scan scan = IndexManagementUtil.newLocalStateScan(maintainers);
>> ScanRanges scanRanges =
>> ScanRanges.create(Collections.singletonList(keys),
>> SchemaUtil.VAR_BINARY_SCHEMA);
>> scanRanges.setScanStartStopRow(scan);
>> scan.setFilter(scanRanges.getSkipScanFilter());
>> HRegion region = this.env.getRegion();
>> RegionScanner scanner = region.getScanner(scan);
>> // Run through the scanner using internal nextRaw method
>> region.startRegionOperation();
>> try {
>> boolean hasMore;
>> do {
>> List<Cell> results = Lists.newArrayList();
>> // Results are potentially returned even when the return value of s.next
>> is false
>> // since this is an indication of whether or not there are more values
>> after the
>> // ones returned
>> hasMore = scanner.nextRaw(results);
>> } while (hasMore);
>> } finally {
>> try {
>> scanner.close();
>> } finally {
>> region.closeRegionOperation();
>> }
>> }
>> }
>> ------------------------------
>>  ------------------------------
>>
>>
>>

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